scholarly journals Ultra-rapid synthesis of the MgCu2 and Mg2Cu Laves phases and their facile conversion to nanostructured copper with controllable porosity; an energy-efficient, reversible process

2021 ◽  
Vol 23 (18) ◽  
pp. 6936-6944
Author(s):  
Zhen Fan ◽  
Gytis Baranovas ◽  
Holly A. Yu ◽  
Robert Szczęsny ◽  
Wei-Ren Liu ◽  
...  
Keyword(s):  
Energy Efficient ◽  
Rapid Synthesis ◽  
Reversible Process ◽  
Laves Phases ◽  
Entire Process ◽  
Metal Plasma ◽  
Porous Copper ◽  
Plasma Methods ◽  
Nanostructured Copper

Porous copper nanoarchitectures are obtained selectively by acid-dealloying of Mg–Cu precursors prepared by microwave-induced-metal-plasma methods; the entire process is reversible.

Probing the microwave interaction mechanisms and reaction pathways in the energy-efficient, ultra-rapid synthesis of tungsten carbide

2012 ◽  
Vol 14 (8) ◽  
pp. 2184 ◽  
Author(s):  
Simon R. Vallance ◽  
Helen J. Kitchen ◽  
Clemens Ritter ◽  
Sam Kingman ◽  
Georgios Dimitrakis ◽  
...  
Keyword(s):  
Tungsten Carbide ◽  
Energy Efficient ◽  
Reaction Pathways ◽  
Rapid Synthesis ◽  
Interaction Mechanisms

Modified Solid-Phase Methods for the Rapid Synthesis of Opioid Peptides

1991 ◽  
Author(s):  
Richard A. Houghten ◽  
◽  
John M. Ostresh ◽  
Suzanne M. Pratt
Keyword(s):  
Opioid Peptides ◽  
Solid Phase ◽  
Rapid Synthesis

Performance Evaluation of AFOD Protocol for Energy Efficient Routing

2011 ◽  
Author(s):  
B. Smitha Shekar ◽  
M. Sudhakar Pillai ◽  
G. Narendra Kumar
Keyword(s):  
Performance Evaluation ◽  
Energy Efficient ◽  
Energy Efficient Routing

On the Preparation of Bovine α-Thrombin

1978 ◽  
Vol 39 (01) ◽  
pp. 193-200 ◽  
Author(s):  
Erwin F Workman ◽  
Roger L Lundblad
Keyword(s):  
Immobilized Enzyme ◽  
Catalytic Properties ◽  
Specific Activity ◽  
Guanidine Hydrochloride ◽  
Low Molecular Weight ◽  
Reversible Process ◽  
Gel Beads ◽  
Tissue Thromboplastin ◽  
C 50 ◽  
Hydrolysis Of

SummaryAn improved method for the preparation of bovine α-thrombin is described. The procedure involves the activation of partially purified prothrombin with tissue thromboplastin followed by chromatography on Sulfopropyl-Sephadex C-50. The purified enzyme is homogeneous on polyacrylamide discontinuous gel electrophoresis and has a specific activity toward fibrinogen of 2,200–2,700 N.I.H. U/mg. Its stability on storage in liquid media is dependent on both ionic strenght and temperature. Increasing ionic strength and decreasing temperature result in optimal stability. The denaturation of α-thrombin by guanidine hydrochloride was found to be a partially reversible process with the renatured species possessing properties similar to “aged” thrombin. In addition, the catalytic properties of a-thrombin covalently attached to agarose gel beads were also examined. The activity of the immobilized enzyme toward fibrinogen was affected to a much greater extent than was the hydrolysis of low molecular weight, synthetic substrates.

Distributed Entropy Energy-Efficient Clustering algorithm for cluster head selection (DEEEC)

2020 ◽  
Vol 39 (6) ◽  
pp. 8139-8147
Author(s):  
Ranganathan Arun ◽  
Rangaswamy Balamurugan
Keyword(s):  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Second Stage ◽  
Energy Efficient Clustering ◽  
Two Stages ◽  
Ch Selection

In Wireless Sensor Networks (WSN) the energy of Sensor nodes is not certainly sufficient. In order to optimize the endurance of WSN, it is essential to minimize the utilization of energy. Head of group or Cluster Head (CH) is an eminent method to develop the endurance of WSN that aggregates the WSN with higher energy. CH for intra-cluster and inter-cluster communication becomes dependent. For complete, in WSN, the Energy level of CH extends its life of cluster. While evolving cluster algorithms, the complicated job is to identify the energy utilization amount of heterogeneous WSNs. Based on Chaotic Firefly Algorithm CH (CFACH) selection, the formulated work is named “Novel Distributed Entropy Energy-Efficient Clustering Algorithm”, in short, DEEEC for HWSNs. The formulated DEEEC Algorithm, which is a CH, has two main stages. In the first stage, the identification of temporary CHs along with its entropy value is found using the correlative measure of residual and original energy. Along with this, in the clustering algorithm, the rotating epoch and its entropy value must be predicted automatically by its sensor nodes. In the second stage, if any member in the cluster having larger residual energy, shall modify the temporary CHs in the direction of the deciding set. The target of the nodes with large energy has the probability to be CHs which is determined by the above two stages meant for CH selection. The MATLAB is required to simulate the DEEEC Algorithm. The simulated results of the formulated DEEEC Algorithm produce good results with respect to the energy and increased lifetime when it is correlated with the current traditional clustering protocols being used in the Heterogeneous WSNs.

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